Generally, there are various data repositories, such as the Gene Expression Omnibus-GEO (https://www.ncbi.nlm.nih.gov/gds), ArrayExpress (https://www.ebi.ac.uk/arrayexpress/), the GDC portal for cancer data (https://gdc.cancer.gov/), as other choises, such as the recount recource (https://jhubiostatistics.shinyapps.io/recount/).

But if you want really to learn transcriptomics from scratch :

https://f1000research.com/articles/5-1384/v1 http://bioconductor.org/help/workflows/RNAseq123/ http://bioconductor.org/help/workflows/RnaSeqGeneEdgeRQL/ http://bioconductor.org/help/workflows/rnaseqGene/ http://bioconductor.org/help/course-materials/

You could also taka a detailed look at the edX series with http://genomicsclass.github.io/book/, as also various Coursera Moocs. As you understand, the list is endless, and you should also have a strong background in statistics and general related concepts,such as statistical inference, distributions etc., prior moving to analyze big data or transcriptomics related.

Best,

Efstathios-Iason